There are many situations in which a joint decision, based on the observations or decisions of multiple individuals, is desired. The challenge is determining when a combined decision is better than each of the individual systems, along with choosing the best way to perform the combination. It has been shown that the diversity between systems plays a role in the performance of their fusion. This study involved several pairs of people, each viewing an event and reporting an observation, along with their confidence level. Each observer is treated as a visual perception system, and hence an associated scoring system is created based on the observer's confidence. A diversity rank-score function on a set of observation pairs is calculated using the notion of cognitive diversity between two scoring systems in the combinatorial fusion analysis framework. The resulting diversity rank-score function graph provides a powerful visualization tool for the diversity variation among a set of system pairs, helping to identify which system pairs are most likely to show improved performance with combination.

中文翻译：

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用于组合人类视觉感知系统的多样性等级得分功能。

在许多情况下，需要基于多个人的观察或决策的共同决策。面临的挑战是确定组合决策何时比每个单独的系统都要好，同时还要选择执行组合的最佳方法。已经表明，系统之间的多样性在其融合性能中起作用。这项研究涉及几对人，每人观看一个事件并报告观察结果，以及他们的置信度。每个观察者都被视为视觉感知系统，因此基于观察者的置信度创建了一个相关的评分系统。使用组合融合分析框架中两个评分系统之间的认知多样性概念，可以计算一组观察对上的多样性等级得分函数。由此产生的多样性等级得分功能图为一组系统对之间的多样性变化提供了强大的可视化工具，有助于识别哪些系统对最有可能在组合中表现出更高的性能。